Video management

ABSTRACT

The disclosure relates to a method of processing a sequence of image frames to reduce its length. One implementation may involve extracting coefficients (e.g., Discrete Cosine Transform coefficients) from components of individual frames, and comparing the resulting coefficients for sequential frames to identify frames having the least change from a prior frame. Also, scene change values for each frame may be calculated and placed in a sorted list to facilitate identification of frames for removal. Frame removal may be conducted in rounds, where a group of pictures (GOP) may only have one frame removed for any given round.

BACKGROUND

Advances in data transmission technologies have allowed contentproviders to transmit multiple streams of content to users, and hundredsof channels of television programming can be delivered. In some cases, auser's viewing experience may automatically hop from one channel toanother. For example, when a television program enters a commercialbreak, the ensuing commercials might actually be carried on a differentchannel or datastream, and the viewer's device (unbeknownst to theviewer) may quickly switch tuning to the different channel for theduration of the commercial, and back to the television program (or toanother channel carrying another commercial) when the commercial ends.To help tuners quickly lock on to the audiovisual signals during suchrapid tuning, video transmission standards call for advertisements tobegin with a few moments of blank/black video and silent audio.Unfortunately, many advertisers provide commercials that lack thesemoments of blank/black video and silent audio. Adding such moments tothe beginning and end of the commercial may result in extending thecommercial's duration, which may make it difficult for the commercial tofit within its allotted time in a commercial break. There remains a needto gracefully make these commercials comply with the video transmissionstandards while also allowing them to fit within their allotted time ina commercial break.

SUMMARY

The following summary is for illustrative purposes only, and is notintended to limit or constrain the detailed description.

Features herein relate to managing a video content comprising a sequenceof image frames by dropping frames in the content. The number of framesto be dropped can depend on the amount of time that is desired to betrimmed from the content. The selection of frames to be dropped canbegin with generating a frame value (e.g., a zero frequency value) foreach frame in the video. The frame value can be the DC coefficientcomponent (e.g., a zero frequency, or top-left element in a transformcoefficient array) from, for example, each 8×8 pixel block extractedfrom the frame after a process such as a Discrete Cosine Transform. Insome embodiments, the coefficients selected may be from the luminance(e.g., luma) component of the image frame, although chrominancecomponents may be used if desired.

When the frame values are generated for the frames in the video content,scene change values may then be generated for each frame in the video bycomparing frame values of neighboring sequential frames. The scenechange value for a frame may represent, for example, how much changed(e.g., visually) between the frame and its previous frame in the videocontent. For example, the scene change values may be determined asfollows:

${C(v)} = {\sum\limits_{n = 1}^{n = h}{\sum\limits_{m = 1}^{m = w}{{abs}\left\lbrack {{{DCv}\left( {m,n} \right)} - {{DCu}\left( {m,n} \right)}} \right\rbrack}}}$

wherein

-   -   C(v)=the scene change value for the v th frame in the video        content,    -   DCv(m,n)=the Discrete Cosine Transform DC component of the m,n        8×8 block of DCT coefficients in the v th frame of the video        content,    -   DCu(m,n)=the Discrete Cosine Transform DC component of the m,n        8×8 block of DCT coefficients in the u th frame of the video        content,        v=u+1,        w=the width of the frame, which may be measured in 8×8 pixel        blocks, and        h=the height of the frame, which may be measured in 8×8 pixel        blocks.

In some embodiments, the frame removal may be conducted in rounds, whereeach group of pictures (GOP) in the video may be limited to having justone (or other predetermined limit) frame removed per round. Theselection of frames for removal may generally seek to remove frames thathave the least amount of change from a prior frame.

In some embodiments, the video may initially include dependent frames,and dependent macroblock portions of frames. The present system mayinitially process these frames to recover their frame values inindependent form, prior to calculating the scene change values andselecting frames for removal.

The summary here is not an exhaustive listing of the novel featuresdescribed herein, and are not limiting of the claims. These and otherfeatures are described in greater detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presentdisclosure will become better understood with regard to the followingdescription, claims, and drawings. The present disclosure is illustratedby way of example, and not limited by, the accompanying figures in whichlike numerals indicate similar elements.

FIG. 1 illustrates an example communication network on which variousfeatures described herein may be used.

FIG. 2 illustrates an example computing device that can be used toimplement any of the methods, servers, entities, and computing devicesdescribed herein.

FIGS. 3A-C illustrate an example concept diagram showing the removal ofselected frames from a video stream.

FIGS. 4A-B illustrate an example algorithm for removing frames from avideo stream.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized, and structuraland functional modifications may be made, without departing from thescope of the present disclosure.

FIG. 1 illustrates an example communication network 100 on which many ofthe various features described herein may be implemented. Network 100may be any type of information distribution network, such as satellite,telephone, cellular, wireless, etc. One example may be an optical fibernetwork, a coaxial cable network, or a hybrid fiber/coax distributionnetwork. Such networks 100 use a series of interconnected communicationlinks 101 (e.g., coaxial cables, optical fibers, wireless, etc.) toconnect multiple premises 102 (e.g., businesses, homes, consumerdwellings, etc.) to a local office or headend 103. The local office 103may transmit downstream information signals onto the links 101, and eachpremises 102 may have a receiver used to receive and process thosesignals.

There may be one link 101 originating from the local office 103, and itmay be split a number of times to distribute the signal to variouspremises 102 in the vicinity (which may be many miles) of the localoffice 103. The links 101 may include components not illustrated, suchas splitters, filters, amplifiers, etc. to help convey the signalclearly, but in general each split introduces a bit of signaldegradation. Portions of the links 101 may also be implemented withfiber-optic cable, while other portions may be implemented with coaxialcable, other lines, or wireless communication paths. By running fiberoptic cable along some portions, for example, signal degradation may besignificantly minimized, allowing a single local office 103 to reacheven farther with its network of links 101 than before.

The local office 103 may include an interface, such as a terminationsystem (TS) 104. More specifically, the interface 104 may be a cablemodem termination system (CMTS), which may be a computing deviceconfigured to manage communications between devices on the network oflinks 101 and backend devices such as servers 105-107 (to be discussedfurther below). The interface 104 may be as specified in a standard,such as the Data Over Cable Service Interface Specification (DOCSIS)standard, published by Cable Television Laboratories, Inc. (a.k.a.CableLabs), or it may be a similar or modified device instead. Theinterface 104 may be configured to place data on one or more downstreamfrequencies to be received by modems at the various premises 102, and toreceive upstream communications from those modems on one or moreupstream frequencies.

The local office 103 may also include one or more network interfaces108, which can permit the local office 103 to communicate with variousother external networks 109. These networks 109 may include, forexample, networks of Internet devices, telephone networks, cellulartelephone networks, fiber optic networks, local wireless networks (e.g.,WiMAX), satellite networks, and any other desired network, and thenetwork interface 108 may include the corresponding circuitry needed tocommunicate on the external networks 109, and to other devices on thenetwork such as a cellular telephone network and its corresponding cellphones.

As noted above, the local office 103 may include a variety of servers105-107 that may be configured to perform various functions. Forexample, the local office 103 may include a push notification server105. The push notification server 105 may generate push notifications todeliver data and/or commands to the various premises 102 in the network(or more specifically, to the devices in the premises 102 that areconfigured to detect such notifications). The local office 103 may alsoinclude a content server 106. The content server 106 may be one or morecomputing devices that are configured to provide content to users attheir premises. This content may be, for example, video on demandmovies, television programs, songs, text listings, etc. The contentserver 106 may include software to validate user identities andentitlements, to locate and retrieve requested content, to encrypt thecontent, and to initiate delivery (e.g., streaming) of the content tothe requesting user(s) and/or device(s).

The local office 103 may also include one or more application servers107. An application server 107 may be a computing device configured tooffer any desired service, and may run various languages and operatingsystems (e.g., servlets and JSP pages running on Tomcat/MySQL, OSX, BSD,Ubuntu, Redhat, HTML5, JavaScript, AJAX and COMET). For example, anapplication server may be responsible for collecting television programlistings information and generating a data download for electronicprogram guide listings. Another application server may be responsiblefor monitoring user viewing habits and collecting that information foruse in selecting advertisements. Yet another application server may beresponsible for formatting and inserting advertisements in a videostream being transmitted to the premises 102. Although shown separately,one of ordinary skill in the art will appreciate that the push server105, content server 106, and application server 107 may be combined.Further, here the push server 105, content server 106, and applicationserver 107 are shown generally, and it will be understood that they mayeach contain memory storing computer executable instructions to cause aprocessor to perform steps described herein and/or memory for storingdata.

An example premises 102 a, such as a home, may include an interface 120.The interface 120 can include any communication circuitry needed toallow a device to communicate on one or more links 101 with otherdevices in the network. For example, the interface 120 may include amodem 110, which may include transmitters and receivers used tocommunicate on the links 101 and with the local office 103. The modem110 may be, for example, a coaxial cable modem (for coaxial cable lines101), a fiber interface node (for fiber optic lines 101), twisted-pairtelephone modem, cellular telephone transceiver, satellite transceiver,local wi-fi router or access point, or any other desired modem device.Also, although only one modem is shown in FIG. 1, a plurality of modemsoperating in parallel may be implemented within the interface 120.Further, the interface 120 may include a gateway interface device 111.The modem 110 may be connected to, or be a part of, the gatewayinterface device 111. The gateway interface device 111 may be acomputing device that communicates with the modem(s) 110 to allow one ormore other devices in the premises 102 a, to communicate with the localoffice 103 and other devices beyond the local office 103. The gateway111 may be a set-top box (STB), digital video recorder (DVR), computerserver, or any other desired computing device. The gateway 111 may alsoinclude (not shown) local network interfaces to provide communicationsignals to requesting entities/devices in the premises 102 a, such asdisplay devices 112 (e.g., televisions), additional STBs or DVRs 113,personal computers 114, laptop computers 115, wireless devices 116(e.g., wireless routers, wireless laptops, notebooks, tablets andnetbooks, cordless phones (e.g., Digital Enhanced CordlessTelephone—DECT phones), mobile phones, mobile televisions, personaldigital assistants (PDA), etc.), landline phones 117 (e.g. Voice overInternet Protocol—VoIP phones), and any other desired devices. Examplesof the local network interfaces include Multimedia Over Coax Alliance(MoCA) interfaces, Ethernet interfaces, universal serial bus (USB)interfaces, wireless interfaces (e.g., IEEE 802.11, IEEE 802.15), analogtwisted pair interfaces, Bluetooth interfaces, and others.

FIG. 2 illustrates general hardware elements that can be used toimplement any of the various computing devices discussed herein. Thecomputing device 200 may include one or more processors 201, which mayexecute instructions of a computer program to perform any of thefeatures described herein. The instructions may be stored in any type ofcomputer-readable medium or memory, to configure the operation of theprocessor 201. For example, instructions may be stored in a read-onlymemory (ROM) 202, random access memory (RAM) 203, removable media 204,such as a Universal Serial Bus (USB) drive, compact disk (CD) or digitalversatile disk (DVD), floppy disk drive, or any other desired storagemedium. Instructions may also be stored in an attached (or internal)hard drive 205. The computing device 200 may include one or more outputdevices, such as a display 206 (e.g., an external television), and mayinclude one or more output device controllers 207, such as a videoprocessor. There may also be one or more user input devices 208, such asa remote control, keyboard, mouse, touch screen, microphone, etc. Thecomputing device 200 may also include one or more network interfaces,such as a network input/output (I/O) circuit 209 (e.g., a network card)to communicate with an external network 210. The network input/outputcircuit 209 may be a wired interface, wireless interface, or acombination of the two. In some embodiments, the network input/outputcircuit 209 may include a modem (e.g., a cable modem), and the externalnetwork 210 may include the communication links 101 discussed above, theexternal network 109, an in-home network, a provider's wireless,coaxial, fiber, or hybrid fiber/coaxial distribution system (e.g., aDOCSIS network), or any other desired network. Additionally, the devicemay include a location-detecting device, such as a global positioningsystem (GPS) microprocessor 211, which can be configured to receive andprocess global positioning signals and determine, with possibleassistance from an external server and antenna, a geographic position ofthe device.

The FIG. 2 example is a hardware configuration, although the illustratedcomponents may be implemented as software as well. Modifications may bemade to add, remove, combine, divide, etc. components of the computingdevice 200 as desired. Additionally, the components illustrated may beimplemented using basic computing devices and components, and the samecomponents (e.g., processor 201, ROM storage 202, display 206, etc.) maybe used to implement any of the other computing devices and componentsdescribed herein. For example, the various components herein may beimplemented using computing devices having components such as aprocessor executing computer-executable instructions stored on acomputer-readable medium, as illustrated in FIG. 2. Some or all of theentities described herein may be software based, and may co-exist in acommon physical platform (e.g., a requesting entity can be a separatesoftware process and program from a dependent entity, both of which maybe executed as software on a common computing device).

One or more aspects of the disclosure may be embodied in acomputer-usable data and/or computer-executable instructions, such as inone or more program modules, executed by one or more computers or otherdevices. Generally, program modules include routines, programs, objects,components, data structures, etc. that perform particular tasks orimplement particular abstract data types when executed by a processor ina computer or other data processing device. The computer executableinstructions may be stored on one or more computer readable media suchas a hard disk, optical disk, removable storage media, solid statememory, RAM, etc. As will be appreciated by one of skill in the art, thefunctionality of the program modules may be combined or distributed asdesired in various embodiments. In addition, the functionality may beembodied in whole or in part in firmware or hardware equivalents such asintegrated circuits, field programmable gate arrays (FPGA), and thelike. Particular data structures may be used to more effectivelyimplement one or more aspects of the disclosure, and such datastructures are contemplated within the scope of computer executableinstructions and computer-usable data described herein.

FIGS. 3A-C are conceptual visualizations of video streams containingsequences of image frames. In FIG. 3A, a video stream 301 is comprisedof a plurality of image frames 302 that are sequentially displayed at apredetermined display rate (e.g., 30 frames per second). The encodingand delivery of the stream 301 may be done in a variety of ways. Oneexample uses MPEG-2 (Moving Pictures Expert Group) encoding, which usesmotion vector-based compression to efficiently represent the stream ofimage frames 302. Using this compression, each frame is categorized aseither an independent frame or a dependent frame. Independent frames arerepresented in the stream by data that is sufficient to generate theframe's complete image without knowledge about neighboring frames in thestream, similar to how a still image picture may be represented. Thefirst frame after a scene change is typically represented using anindependent frame.

Dependent frames, as their name implies, are represented by data that isdependent on another frame in the stream, such as a correspondingindependent frame, to generate the complete image of the dependentframe. The data representing a dependent frame may simply indicatechanges with respect to a prior frame. For example, the data for adependent frame may simply indicate that a first portion of the imageremains unchanged from the prior frame, and that a second portion movessome distance (e.g., 3 pixels) to the right. In this manner, the datarepresenting the dependent frame can omit the full details for the firstportion of the dependent frame's image, thereby reducing the amount ofdata that is needed to be transmitted.

In the MPEG-2 standard, which is one example audiovisual standard usableherein, independent frames are referred to as Intra-coded picture frames(I-frames), while dependent frames are referred to as either Predictedpicture frames (P-frames), or a Bi-directional predicted picture frames(B-frames). A P-frame is dependent on a prior frame in the stream, whilea B-frame is dependent on both a prior and a subsequent frame in thestream.

In some embodiments, this motion vector-based compression can be done onan even smaller scale than a frame. For example, a single image framemay be divided into smaller sub-frames, and the same VP/B-frametreatment may be performed at the sub-frame level. For example, thesub-frame can be an 8×8 collection of pixels, a 16×16 collection ofpixels, or any other desired portion of the frames. In MPEG-2, so-called“macroblocks” may be formed by performing discrete cosine transforms onblock portions of the frame. There, a 16×16 macroblock may be comprisedof 16×16 luma (Y) samples and 8×8 chroma (Cb and Cr) samples.

As noted above, a user's video device (e.g., gateway, smartphone,Digital Video Recorder, Set-Top Box, etc.) may need to tune to differentchannels (e.g., different Quadrature Amplitude Modulated (QAM) channelson different frequencies, different logical streams carried on a singleQAM channel, different Internet Protocol streams, etc.) when presentingthe user with video commercials during a break in scheduled programming(e.g., a television program, movie, etc.), and may need to return to anoriginal channel or stream when the commercial break ends and thescheduled programming resumes. To allow smoother and quick transitions,the commercial break content may be shortened to allow moments of silentaudio and blank and/or black video at the beginning and end of thecommercials. So, for example, if the commercial stream 301 is 30-secondsin duration, but the content provider wishes to have 0.5 seconds ofsilence/black on either end of the commercial, then the 30-secondcommercial needs to be reduced to 29 seconds in duration. To supportthis using the features described herein, certain frames 303 (FIG. 3B)in the stream may be selected for removal based on how disruptive theirremoval would be. The resulting shortened stream 304 (FIG. 3C) may thenbe transmitted for tuning and presentation to the user at theappropriate time.

FIGS. 4A and B illustrate an example process by which frames, such asthe selected frames 303, may be chosen for removal to create theshortened stream 304. The process may be performed by any one or morecomputing devices capable of video delivery, and in the FIG. 1 examplenetwork, the process may be performed at least in part by the contentserver 106 computing device.

Beginning in step 401, the computing device may receive a video stream301 (or a file) and determine the frame rate (m) of the original videostream 301. This may be, for example, identified by information in thevideo stream 301 file. In step 402, the computing device may determinethe amount of time (t) that is to be removed from the video stream 301.For example, a 30-second segment, such as a commercial, may need to bereduced by one second, to result in a 29-second commercial.

In step 403, the computing device may determine the number of frames (Z)that will need to be removed from the video stream 301 to achieve thedesired reduction in time (t). This calculation may be as follows:(Z=t*m).

In step 404, the computing device may begin to process each frame (e.g.,in a looping fashion) in the stream 301 and generate correspondingcomparison data that will be used in the eventual frame selection. Ingeneral, the frame selection algorithm may seek to identify the frameswhose removal would cause the least amount of disruption to theresulting video stream, so that the shortened stream 304 will provide asclose an experience as possible to the original stream 301. Thisselection algorithm may need to compare data, the comparison data,representing visual elements of each of the various frames in the stream301 to make this selection.

In one example embodiment, the selection of frames may be based oncomparisons of values representing portions of the video frame, such asthe DC coefficient values for subsampled blocks of the frame. In oneexample embodiment, luminance (Y) components of blocks (e.g., 8×8 lumablocks) in an image may be processed through a Discrete Cosine Transform(DCT), resulting in an array of values, such as luminance DC coefficientvalues, for subsampled blocks of the frame, and these values may becompared in the eventual selection of frames. The values may be storedin the video file according to some video formats, although in othervideo formats the values may be obtained by performing the DCT on otherdata representing the frame. The details of this processing arediscussed further below with regard to step 407.

The loop beginning in step 404 may sequentially step through each framein the stream 301. In step 405, the computing device may select the nextframe for processing. This selection may include maintaining a record ofthe sequence of frames in the video stream 301, identifying the onesthat have been processed to generate the comparison data for that frame,and selecting the earliest frame in the sequence that has not yet beenprocessed to generate its comparison data.

In step 406, the computing device may determine whether the selectedframe is an independent frame, or I-frame. If the selected frame is anindependent frame, then in step 407, the computing device may proceed togenerate the comparison data for that frame by first identifyingportions, such as each 8×8 luma block of DCT coefficients, in the frame.

The comparison data, as will be discussed below, may be used to comparesuccessive frames to identify an amount of change between the twoframes. In some embodiments, the comparison data may be the DCcoefficients that result when luminance components of a macroblock(e.g., a luma block) are processed using a Discrete Cosine Transform(DCT). Although the luminance component is used herein as an example,other features of an image frame may be used as well. For example, achrominance component may be used instead.

In step 408, the computing device may perform a process such as aDiscrete Cosine Transform (DCT) on the portion of the frame (e.g., an8×8 pixel luma block). This step may be omitted, however, if the sourcevideo is in a compressed format that already includes DCT-transformedluma block information. In step 409, the computing device may then storethe DC coefficient of the result of the DCT for each portion (e.g., theluma DCT block). As a result, the computing device may store an arrayidentifying the frame content, such as the luminance component DCT DCcoefficients for all luma blocks in the frame. If the original frame is720×480 pixels, and the luma blocks represent 8×8 pixel blocks, thenthis may result in a 90×60 array of luminance component DCT DCcoefficients for the frame. Although DCT processes are used as anexample above, other processes may be used to represent the content of aparticular portion (or the entirety) of a frame for comparison purposes.

In step 406, if the selected frame is a dependent frame, then theluminance values for the various macroblocks in the frame may depend onneighboring frame(s), and may first need to be decoded before they canbe processed to obtain the coefficients discussed above. Step 410 maybegin a looping process to ensure that the luminance componentcoefficient values for all of the luma blocks in the current frame aredecoded and available for use in the step 409 storing of the component(e.g., the DC component) from each luma block. The looping process maysequentially process each macroblock in the frame, and in step 411, thecomputing device may select the next macroblock for processing.

In step 412, the computing device may determine whether the selectedmacroblock is an independent macroblock. As described above, frames maybe independent or dependent, based on whether the frame's data can bederived without reference to a neighboring frame's data. The sameapproach may be used at the macroblock level. An independent macroblockmay be represented by data that can be used to generate the macroblock'sportion of the frame, while a dependent macroblock may be represented bydata that refers to one or more macroblocks in reference pictures.

If the macroblock is dependent on another macroblock, then in step 413,the computing device may determine what other macroblock(s), or theirpredicted macroblock(s), are needed to decode the current macroblock. Instep 414, the computing device may retrieve the data for those otherpredicted macroblocks, and may use that data to decode the DC componentinformation for each 8×8 luma block in the current macroblock. Theprocess may then return to step 410, and repeat until the computingdevice stores an array of data, such as the luminance component DCT DCcoefficients, for the frame. At this point, the computing device nowstores sufficient information for the dependent frame to generate itsdisplay without further reference to neighboring frame(s). From there,the process may proceed to step 407, to generate the comparison data,e.g., the luminance DC component, for each of the macroblocks in theframe, and the two loops above may continue processing until thecomputing device has generated comparison data values, such as luminancecomponent DCT DC coefficient values, for each frame in the video.

Returning to step 404, when all frames have been processed to generatethe comparison data, the computing device may proceed to step 415, andbegin a process of comparing frames to select frames for removal. FIG. 4b illustrates this portion of the process. In step 415, the scene changevalue C(v) for each frame may be calculated as a sum of the differencesin the comparison values (e.g., the luminance DC component values)between corresponding sampling points in the frame and the immediatelypreceding frame. The determination for C(v) of a vth image frame in asequence of image frames may be expressed as follows:

${C(v)} = {\sum\limits_{n = 1}^{n = h}{\sum\limits_{m = 1}^{m = w}{{abs}\left\lbrack {{{DCv}\left( {m,n} \right)} - {{DCu}\left( {m,n} \right)}} \right\rbrack}}}$

wherein

-   -   C(v)=the scene change value for the vth frame in the video        content,    -   DCv(m,n)=the Discrete Cosine Transform DC component of the m,n        8×8 block of DCT coefficients in the vth frame of the video        content,    -   DCu(m,n)=the Discrete Cosine Transform DC component of the m,n        8×8 block of DCT coefficients in the uth frame of the video        content,        v=u+1,        w=the width of the frame, measured in 8×8 pixel blocks (8×8        pixel blocks are an example, and in alternate embodiments any        desired sample size may be used), and        h=the height of the frame, measured in 8×8 pixel blocks.

In this example, the video content may be a sequence of image frames. Asindividual image frames are removed, the same calculations may be madefor the image frames in the remaining sequence of image frames.

The first frame may have its scene change value compared against zerovalues, resulting in a relatively high value of change.

From step 415, the computing device may determine and optionally storein memory a scene change value C(v) for each frame in the video, and mayproceed to step 416, in which the various frames may be grouped intogroups of pictures (GOP). In video coding, a GOP may be a collection offrames that have a common independent frame. For example, one GOP maycomprise an independent frame and all of its corresponding dependentframes.

In step 417, the computing device may create a ranked frame list thatranks the various frames according to their scene change values C(v),from lowest to highest.

In step 418, the computing device may then create a GOP round list that,at first, is simply a copy of the ranked frame list. The ranked framelist and GOP round list may be used in the ensuing steps to remove theframes that have the lowest scene change value, but to also evenly (tothe extent possible) distribute the removal of frames across the variousGOPs, so that no single GOP becomes disproportionately affected byhaving too many of its frames removed.

In step 419, the computing device may examine the GOP round list, andidentify the first one on the list (i.e., the frame with the lowestscene change value C(v)) for removal. In step 420, the selected framemay then be removed from the ranked frame list.

In step 421, the computing device may determine the GOP to which theselected frame belonged, and may remove all of the GOP's other framesfrom the GOP round list.

The removal of the selected frame now means that the scene change valueC(v) calculated for the frame that followed the selected frame in thesource video, the next frame, is outdated (since that scene change valuecalculated a difference using the now-removed frame's DC coefficientvalues). So in step 422, the computing device may recompute the scenechange value C(v) for that next frame, but instead of comparing the nextframe's coefficient values with those of the selected frame, thecomputing device may compare the values of the next frame with the framethat preceded the selected frame in the source video. In someembodiments, this recomputing may be optional, since the small change inscene often means that the recomputed value will be nearly the same asbefore. The recomputing may be skipped if the scene change value issmaller than a predetermined minimum change value, and this optionalskipping may help reduce processing demand.

In step 423, the computing device may determine whether it has removedthe desired number of frames (Z) from the source video. If it has notyet removed enough frames, then in step 424, the computing device maydetermine whether the GOP round list is empty. If the GOP round list isnot empty, then the process may return to step 419 to select the nextframe for removal. If the GOP round list was empty in step 424, then thecomputing device may proceed to step 425, and copy the current rankedframe list (which omits the frames that have been removed so far in theprocess) to create a new GOP round list, and the process may then returnto step 419 to select the next frame for removal.

When the necessary number of frames (Z) has been removed, then thecomputing device may proceed to step 426, and encode a new video filecontaining just the frames remaining in the ranked frame list, and maygenerate new time stamps for the resulting image frames. In step 427,the computing device may encode a new audio soundtrack, based on theaudio for the original video, to accompany the reduced set of frames inthe video. The encoding of the new audio soundtrack may simply involveskipping portions of audio that accompanied the removed frames.

In step 428, the computing device may add black frames and silent audioportions to the beginning and end of the new video file. This mayinvolve, for example, adding a number (Z) of frames equal to the numberof removed frames, and the addition may be evenly split between thebeginning and end of the new video file.

In step 429, the computing device may then take the new video file, andtransmit it to receiving user devices instead of the original videofile. This may entail, for example, remultiplexing the new video file inother streams or channels according to the same schedule used for theoriginal video file.

Although example embodiments are described above, the various featuresand steps may be combined, divided, omitted, rearranged, revised and/oraugmented in any desired manner, depending on the specific outcomeand/or application. Various alterations, modifications, and improvementswill readily occur to those skilled in art. For example, the exampleprocess above uses luminance components, while other embodiments may usechrominance components instead. The example above also limits the frameremoval to one frame per GOP per round. That limit can be revised toallow more than one frame from a GOP to be removed per round.

Additional alterations, modifications, and improvements as are madeobvious by this disclosure are intended to be part of this descriptionthough not expressly stated herein, and are intended to be within thespirit and scope of the disclosure. Accordingly, the foregoingdescription is by way of example only, and not limiting. This patent islimited only as defined in the following claims and equivalents thereto.

I/we claim:
 1. A method, comprising: obtaining luminance componentcoefficient values for a plurality of image frames in a sequence ofimage frames; generating a scene change value for each of the pluralityof image frames by comparing the coefficient values for sequential onesof the plurality of image frames; ranking the plurality of image framesaccording to their scene change values; and selecting one or more of theimage frames for removal based on the ranked plurality of image frames.2. The method of claim 1, wherein the scene change values are generatedaccording to the following formula:${C(v)} = {\sum\limits_{n = 1}^{n = h}{\sum\limits_{m = 1}^{m = w}{{abs}\left\lbrack {{{DCv}\left( {m,n} \right)} - {{DCu}\left( {m,n} \right)}} \right\rbrack}}}$wherein C(v)=a scene change value for a vth image frame, DCv(m,n)=aDiscrete Cosine Transform DC component of an m,n 8×8 block of DCTcoefficients in the vth image frame, DCu(m,n)=a Discrete CosineTransform DC component of an m,n 8×8 block of DCT coefficients in a uthframe, v=u+1, w=a width of an image frame, and h=a height of an imageframe.
 3. The method of claim 1, further comprising generating amodified version of the sequence of image frames by removing theselected one or more image frames, and inserting a corresponding set ofblack frames.
 4. The method of claim 1, wherein obtaining the luminancecomponent coefficient values comprises extracting a first pixel blockcoefficient from a discrete cosine transformed block.
 5. The method ofclaim 1, wherein the selecting further comprises: identifying groups ofpictures (GOPs) in the sequence of image frames; and conducting frameselection in rounds, and limiting selections from each GOP to one frameper round.
 6. The method of claim 1, wherein the selecting furthercomprises selecting an image frame having a least amount of scene changecompared to a preceding image frame.
 7. The method of claim 1, furthercomprising using one or more chrominance components to generate thecoefficient values.
 8. The method of claim 1, further comprisingdetermining whether a source file of the sequence of image framescontains dependent frames, and in response to determining that thesource file contains dependent frames, decoding the dependent framesprior to generating the scene change values.
 9. The method of claim 1,further comprising determining that a source file of the sequence ofimage frames does not contain any dependent frames.
 10. A method,comprising: determining that a sequence of image frames is to beshortened; and selecting image frames of the sequence of image framesfor removal based on comparisons between Discrete Cosine Transform (DCT)DC coefficients of sequential image frames in the sequence of imageframes.
 11. The method of claim 10, further comprising: identifyinggroups of pictures (GOP) among the frames in the sequence of imageframes; and conducting frame removal in rounds, wherein the frameremoval is limited to one frame per GOP per round.
 12. The method ofclaim 10, wherein the Discrete Cosine Transform (DCT) DC coefficientsare extracted from luminance component DCT values of the image frames.13. The method of claim 10, wherein the Discrete Cosine Transform (DCT)DC coefficients are extracted from chrominance component DCT values ofthe image frames.
 14. The method of claim 10, further comprisingdecoding dependent image frames in the sequence of image frames prior toselecting image frames of the sequence of image frames for removal. 15.The method of claim 10, further comprising: performing the comparisonsby generating a total of differences in DC coefficient from each 8×8 DCTcoefficients block between corresponding sample portions of sequentialimage frames.
 16. The method of claim 15, wherein the sample portionsare blocks of pixels.
 17. The method of claim 15, further comprisingcalculating a total of differences in DC coefficients from each 8×8 DCTcoefficients block between a second image frame and a first image framein the sequence of image frames, and assigning the total of differencesfor both the first and second image frames in the sequence of imageframes, and using the total of differences in the selecting of imageframes.
 18. The method of claim 10, further comprising generating scenechange values for each of the image frames in the sequence of imageframes according to the following formula:${C(v)} = {\sum\limits_{n = 1}^{n = h}{\sum\limits_{m = 1}^{m = w}{{abs}\left\lbrack {{{DCv}\left( {m,n} \right)} - {{DCu}\left( {m,n} \right)}} \right\rbrack}}}$wherein C(v)=a scene change value for a vth frame, DCv(m,n)=a DiscreteCosine Transform DC component of an m,n 8×8 block of DCT coefficients inthe vth image frame, DCu(m,n)=a Discrete Cosine Transform DC componentof an m,n 8×8 block of DCT coefficients in a uth image frame, v=u+1, w=awidth of an image frame, and h=a height of an image frame.
 19. A method,comprising: determining a scene change value for each of a plurality ofimage frames in a sequence of image frames according to the followingformula:${C(v)} = {\sum\limits_{n = 1}^{n = h}{\sum\limits_{m = 1}^{m = w}{{abs}\left\lbrack {{{DCv}\left( {m,n} \right)} - {{DCu}\left( {m,n} \right)}} \right\rbrack}}}$wherein C(v)=a scene change value for a vth image frame, DCv(m,n)=aDiscrete Cosine Transform DC component of an m,n 8×8 block of DCTcoefficients in the vth image frame, DCu(m,n)=a Discrete CosineTransform DC component of an m,n 8×8 block of DCT coefficients in a uthimage frame, v=u+1, w=a width of an image frame, and h=a height of animage frame; and using the scene change values for the plurality ofimage frames to select image frames for removal from the sequence ofimage frames.
 20. The method of claim 19, further comprising extractinga pixel block's luminance DC component, and using the extractedluminance DC component to determine the DCv(m,n) value.